• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.173-179
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• 2017

Advanced countries, animal wastes are produced using bioenergy and methane gas technology. In Korea, many researches are being actively carried out to develop livestock manure as a resource technology rather than a animal waste. However, the production of bio-gas using livestock manure is still in the process of development of functional livestock and compost because of low economic efficiency with livestock manure recycling technology. In this paper, in order to accurately estimate the manure output, It will calculate the manure excretion if you have finished input the number of pigs. In addition, we simulated the fertilization rate of three elements of NPK fertilizer per 100 square meters automatically.

• Journal of the Korea Safety Management & Science
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• v.9 no.1
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• pp.197-211
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• 2007

The power of semiconductor, Korea is continuously constructing semiconductor production line for keeping a front-runner status. however, studies and data about potential risks in semiconductor factory are still short. If fire does not initially suppressed, the fire causes a great damage. To decrease fire risk factors, in addition to fire fighting safety equipment, more important thing is how to design and construct fire protection system. The current fire protection codes about semiconductor factory come under functional law, and this law is short of consideration about particularity of factory. The existing prescriptive fire codes depending on experience compose without evident engineering verifications, thus equipments which is created by the current prescriptive fire code may bring about a variety of problems. For example, the design under the current regulation can not cope with the excessive investments, low efficiencies, and the diversifying construction designs and be applied to the quick changes of new technologies. Ergo, an optimal design for fire protection is to equip fire protection arrangements with condition and environment of production field. Manufacturing factory of semiconductors is a windowless airtight space. And for cleanliness, there exists strong flow of cooperation. Therefore, there is a need for fire safety design that meets the characteristic of a clean room. Accordingly, we are to derive smoke flow according to cooperation process within a clean room and construction plan of an optimal sensor system. In this study, in order to confirm the performance of proposed smoke-exhaust equipment and suggest efficient smoke exhaust device when there is a fire of 1MW of methane in the clean room of company H, we have implemented fire simulation using fluid dynamics computation.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.23-30
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• 2020

In this study, the relationship between natural gas (NG) data and gas-related environmental elements was performed using machine learning algorithms to predict the level of gas leakage risk without directly measuring gas leakage data. The study was based on open data provided by the server using the IoT-based remote control Picarro gas sensor specification. The naturel gas leaks into the air, it is a big problem for air pollution, environment and the health. The proposed method is multivariate outlier removing method based Random Forest (RF) classification for predicting risk of NG leak. After, unsupervised k-means clustering, the experimental dataset has done imbalanced data. Therefore, we focusing our proposed models can predict medium and high risk so best. In this case, we compared the receiver operating characteristic (ROC) curve, accuracy, area under the ROC curve (AUC), and mean standard error (MSE) for each classification model. As a result of our experiments, the evaluation measurements include accuracy, area under the ROC curve (AUC), and MSE; 99.71%, 99.57%, and 0.0016 for MOL_RF respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.81-86
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• 2019

Metal oxide/graphene composites have been known as promising functional materials for advanced applications such as high sensitivity gas sensor, and high capacitive secondary battery. In this study, tin dioxide ($SnO_2$) nanostructures were grown on chemically synthesized graphene nanosheets using a two-zone horizontal furnace system. The large area graphene nanosheets were synthesized on Cu foil by thermal chemical vapor deposition system with the methane and hydrogen gas. Chemically synthesized graphene nanosheets were transferred on cleaned $SiO_2$(300 nm)/Si substrate using the PMMA. The $SnO_2$ nanostuctures were grown on graphene nanosheets at $424^{\circ}C$ under 3.1 Torr for 3 hours. Raman spectroscopy was used to estimate the quality of as-synthesized graphene nanosheets and to confirm the phase of as-grown $SnO_2$ nanostructures. The surface morphology of as-grown $SnO_2$ nanostructures on graphene nanosheets was characterized by field-emission scanning electron microscopy (FE-SEM). As the results, the synthesized graphene nanosheets are bi-layers graphene nanosheets, and as-grown tin oxide nanostructures exhibit tin dioxide phase. The morphology of $SnO_2$ nanostructures on graphene nanosheets exhibits complex nanostructures, whereas the surface morphology of $SnO_2$ nanostructures on $SiO_2$(300 nm)/Si substrate exhibits simply nano-dots. The complex nanostructures of $SnO_2$ on graphene nanosheets are attributed to functional groups on graphene surface.